The present invention relates in general to artificial intelligence systems and in particular to a new and useful device which combines artificial neural network ("ANN") learning techniques with fuzzy logic techniques.
Both neural network learning techniques and fuzzy logic techniques are known. In fact, prior combinations of the two techniques are known as well, as for example U.S. Pat. No. 5,179,624 issued Jan. 12, 1993 to Amano ("Speech recognition apparatus using neural network and fuzzy logic"), which is incorporated herein by reference.
Both techniques attempt to replicate or improve upon a human expert's ability to provide a response to a set of inputs. ANNs extract knowledge from empirical databases used as training sets and fuzzy logic usually extracts rules from human experts.
In very brief summary, neural network techniques are based on observation of what an expert does in response to a set of inputs, while fuzzy logic techniques are based on eliciting what an expert says he will do in response to a set of inputs. Many authors, including Applicant, have recognized the potential value of combining the capabilities of the two techniques.
Applicant is the author of Chapters 3, 10 and 13 of D. White & D. Sofge, Handbook of Intelligent Control: Neural, Fuzzy and Adaptive Approaches, Van Nostrand, 1992, ("HIC"), which was published no earlier than Sep. 1, 1992 and which contains disclosure of a number of novel inventions which will be summarized and claimed herein. The entirety of those chapters are incorporated herein by reference.
The invention described and claimed herein comprises an Elastic Fuzzy Logic ("ELF") System in which classical neural network learning techniques are combined with fuzzy logic techniques in order to accomplish artificial intelligence tasks such as pattern recognition, expert cloning and trajectory control. The ELF system may be implemented in a computer provided with multiplier means and storage means for storing a vector of weights to be used as multiplier factors in an apparatus for fuzzy control. The invention further comprises novel techniques and apparatus for adapting ELF Systems and other nonlinear differentiable systems and a novel gradient-based technique and apparatus for matching both predicted outputs and derivatives to actual outputs and derivatives of a system.